A video may be a presentation of a plurality of images shown in sequence over a period of time. The video may be used as a basis for broadcasting a variety of events. For example, the events may be live events such as sporting events (e.g., baseball, football, basketball, soccer, hockey, etc.), concert events, etc. or pre-recorded events such as broadcast programs or shows. While broadcasting the video of the event, the images may be processed for a variety of reasons. For example, the video may be shown with enhancements or include further features within the images of the video. In a specific enhancement, during a broadcast of a football game, a first-down line feature may be used in which a fluorescent yellow line appears on the field. To properly provide these enhancements or further features, the images may be processed to determine background components and foreground components, when applicable. For example, in a sporting event, the background component may be a stadium or field while the foreground components may include the athletes. Accordingly, the first-down line feature may be properly superimposed over only the background components of the image so that it does not occlude or block the foreground components.
There are different manners for the foreground components to be differentiated from the background components within an image. That is, there are a variety of mechanisms that may be used to determine objects in the foreground and remaining portions that comprise the background. One consideration behind using the different mechanisms is whether an image-capturing device (e.g., camera) is moving. Some background/foreground differentiation mechanisms were designed with this consideration as a basis.
In a first example of an image analysis mechanism, a background modeling based method may be used in which a training image sequence is studied to determine what is background, typically resulting in a reference image representative of the background. A subsequent image may include a foreground object that may be determined based upon the reference background image. This type of background modeling based method may be considered an inter-frame processing method. The background modeling based method is often associated and more efficient with images that are captured with a static image-capturing device (e.g. stationary camera). In view of the reference images, those skilled in the art will understand that when the image-capturing device is in motion, there are potentially significant further processing requirements to perform the background/foreground functionality. When a broadcast is shown live such as a sporting event, the background/foreground functionality must be performed within an acceptable time. Even when the image-capturing device is static, there may be other inadvertent errors that may occur such as a ghosting effect.
In a second example of an image analysis mechanism, a feature-based segmentation method may be used in which an image-by-image analysis is performed to determine what comprises the background and foreground. This type of background analysis where each image is analyzed may be considered an intra-frame processing method. The feature-based segmentation method is often associated with images that are captured with a moving image-capturing device. When intra-frame processing is used, those skilled in the art will understand that when the image-capturing device is static, there may be significant unnecessary processing steps that are performed when using this type of background processing mechanism. Again, when a broadcast is shown live, the background/foreground functionality must be performed within an acceptable time.
Therefore, although there are different manners of performing image processing to determine the foreground and background within an image, there are limitations and drawbacks associated with all these manners.